Chromosomal abnormalities associated with autism or autism spectrum-disorders have been reported in 56 different regions involving all 22 autosomes plus both sex chromosomes. The completion of the mapping of the human genome has enabled the development of new whole genome BAG microarrays that allow simultaneous examination of the entire human genome for chromosomal abnormalities involving changes in dosage (i.e. deletions or duplications). This technique is termed array comparative genomic hybridization (aCGH). Routine cytogenetics has a resolution of approximately 3-4 MB while the whole genome microarrays have a resolution of -150 kb. The availability of these microarrays allows for the first time the ability to screen for constitutional chromosomal abnormalities related to autism on a whole genome scale. The hypothesis to be tested is that chromosomal imbalances detected using aCGH will identify both large abnormalities plus new smaller abnormalities that were previously undetectable using older techniques. Aim #1)Array CGH using a 6k microarray will be performed on 800 subjects with autism or autism spectrum disorder. To determine whether the abnormality is associated with autism, a case control study using 800 normal controls will also be perfomed. Aim #2) In silico analysis of the abnormal regions identified in aim #1 will be performed using the UCSC genome bioinformatics website. The regions will be characterized for the presence of microsatellites for confirmation studies, candidate genes, predicted genes and regions of strong conservation between species. Aim #3) All subjects that contain a region or regions with abnormal dosage using array CGH will be confirmed using both molecular and cytogenetic techniques. Microsatellite analysis of the child and both parents will be used to confirm the presence and size of the abnormality and the parental origin for potentially imprinted regions. Aim #4) Statistical analysis. The chisquared contingency table test will be performed and the significance of the result assessed using a Monte Carlo approach to determine the statististical significance of chromosomal imbalances. These data will be valuable in both identifying polymorphic variants in normal human control samples and also identifying chromosomal dosage imbalances that are associated with autism.